Variational-quantum-eigensolver-inspired optimization for spin-chain work extraction

TL;DR

This paper introduces a variational quantum algorithm inspired by VQE to optimize work extraction from quantum spin chains, considering hardware limitations on available unitaries, and demonstrates the importance of connectivity in quantum circuits for efficiency.

Contribution

It develops a VQE-inspired method for optimizing energy extraction from quantum sources with limited unitaries, tailored to specific hardware connectivity constraints.

Findings

Optimal work extraction is achieved with circuits having first-neighbor connectivity.

Connectivity significantly impacts the efficiency of energy extraction.

The approach adapts to different quantum hardware architectures.

Abstract

The energy extraction from quantum sources is a key task to develop new quantum devices such as quantum batteries (QB). In this context, one of the main figures of merit is the ergotropy, which measures the maximal amount of energy (as work) that can be extracted from the quantum source by means of unitary operations. One of the main issues to fully extract energy from the quantum source is the assumption that any unitary operation can be done on the system. This assumption, in general, fails in practice since the operations that can be done are limited and depend on the quantum hardware (experimental platform) one has available. In this work, we propose an approach to optimize the extractable energy inspired by the variational quantum eigensolver (VQE) algorithm. In this approach, we explicitly take into account a limited set of unitaries by using the hardware efficient asatz (HEA) class of parameterized quantum circuits. As a QB we use an one-dimensional spin chain described by a family of paradigmatic first neighbor Hamiltonians such as the $XXX$,$XXZ$, $XYZ$, $XX$, $XY$ and transverse Ising models. By building our parameterized quantum circuits assuming that different types of connectivity may be available depending on the quantum hardware, we numerically compare the efficiency of work extraction for each model. Our results show that the best efficiency is generally obtained with quantum circuits that have connectivity between first neighbor spins.